Software Sale Live

Softwares MegaODA and CTA, as well as a .pdf  of the book Maximizing Predictive Accuracy, are for sale on the Purchase page for $9.99.


 

To run MegaODA and CTA softwares within Stata refer to these pages. Dr. Ariel Linden created and published the Stata programs for these softwares.

ODA, LLC will publish instructional videos to YouTube on these softwares regularly.

Implementing ODA from Within Stata: A Priori Hypothesis, Three-Category Class Variable, Four-Level (Integer) Attribute

Paul R. Yarnold & Ariel Linden

Optimal Data Analysis LLC & Linden Consulting Group LLC

This paper describes how to test a directional (confirmatory) hypothesis for a design relating a three-category class (“dependent”) variable and a four-level categorical ordinal attribute (“Likert-type independent variable”) vis-à-vis the new Stata package for implementing ODA.

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Implementing ODA from Within Stata: Directional Hypothesis, Multicategorical Class Variable, Ordinal Attribute

Paul R. Yarnold & Ariel Linden

Optimal Data Analysis LLC & Linden Consulting Group LLC

This paper describes how to assess a confirmatory (directional) hypothesis for a design involving a multicategorical class (“dependent”) variable and an ordinal attribute (“independent variable”) using the new Stata package for implementing ODA.

View journal article

Implementing ODA from Within Stata: Directional Hypothesis, Multicategorical Class Variable and Attribute

Paul R. Yarnold & Ariel Linden

Optimal Data Analysis LLC & Linden Consulting Group LLC

This paper demonstrates how to evaluate a confirmatory (directional) hypothesis for a design involving a multicategorical class (“dependent”) variable and a multicategorical attribute (“independent variable”) using the new Stata package for implementing ODA.

View journal article

Implementing ODA from Within Stata: Nondirectional, Multicategorical Class Variable, Multicategorical Attribute

Paul R. Yarnold & Ariel Linden

Optimal Data Analysis LLC & Linden Consulting Group LLC

This paper describes how to evaluate an exploratory (nondirectional) hypothesis for a design involving a multicategorical class (“dependent”) variable and a multicategorical attribute (“independent variable”) using the new Stata package for implementing ODA.

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Implementing ODA from Within Stata: Confirmatory Hypothesis, Binary Class Variable, Continuous Attribute

Paul R. Yarnold & Ariel Linden

Optimal Data Analysis LLC & Linden Consulting Group LLC

This paper describes how a confirmatory (a priori, directional, one-tailed) hypothesis involving a binary (dichotomous) class variable and continuous (interval or ratio) attribute is evaluated via MegaODA software using the new Stata package implementing ODA analysis.

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